A simplified U-Net WGAN learns to map desired electromagnetic responses to switchable dual-band FSS topologies, achieving over 90% validation accuracy and passing full-wave and experimental checks.
Phase-to-pattern inverse design for a fast realization of a functional metasurface by combining a deep neural network and a genetic algorithm
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WGAN based Inverse Design of Active Dual Band FSS with Switchable Transmission
A simplified U-Net WGAN learns to map desired electromagnetic responses to switchable dual-band FSS topologies, achieving over 90% validation accuracy and passing full-wave and experimental checks.